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The key-value (KV) cache is the dominant memory bottleneck during Transformer inference, yet little is known theoretically about how aggressively it can be compressed before multi-step reasoning degrades. We study this through $k$-hop…

Machine Learning · Computer Science 2026-04-21 Xiao Wang

Estimating quantiles is one of the foundational problems of data sketching. Given $n$ elements $x_1, x_2, \dots, x_n$ from some universe of size $U$ arriving in a data stream, a quantile sketch estimates the rank of any element with…

Data Structures and Algorithms · Computer Science 2024-04-08 Meghal Gupta , Mihir Singhal , Hongxun Wu

Recently, supervised hashing methods have attracted much attention since they can optimize retrieval speed and storage cost while preserving semantic information. Because hashing codes learning is NP-hard, many methods resort to some form…

Machine Learning · Computer Science 2017-12-05 Zihao Hu , Xiyi Luo , Hongtao Lu , Yong Yu

A long-standing open question in the algorithms and complexity literature is whether there exist sorting circuits of size $o(n \log n)$. A recent work by Asharov, Lin, and Shi (SODA'21) showed that if the elements to be sorted have short…

Data Structures and Algorithms · Computer Science 2021-11-09 Wei-Kai Lin , Elaine Shi

We present a refined analysis of the classic Count-Sketch streaming heavy hitters algorithm [CCF02]. Count-Sketch uses O(k log n) linear measurements of a vector x in R^n to give an estimate x' of x. The standard analysis shows that this…

Data Structures and Algorithms · Computer Science 2013-10-22 Gregory T. Minton , Eric Price

The key-value (KV) cache dominates memory bandwidth and footprint in long-context autoregressive inference. Recent rotation-preconditioned codecs (TurboQuant, PolarQuant) show that a structured random rotation followed by a per-coordinate…

Machine Learning · Computer Science 2026-05-21 Mark Boss , Vikram Voleti , Simon Donné , Shimon Vainer

In the $k$-cut problem, we are given an edge-weighted graph and want to find the least-weight set of edges whose deletion breaks the graph into $k$ connected components. Algorithms due to Karger-Stein and Thorup showed how to find such a…

Data Structures and Algorithms · Computer Science 2019-11-22 Anupam Gupta , Euiwoong Lee , Jason Li

There is a common problem of operating on hash values of elements of some database. In this paper there will be analyzed informational content of such general task and how to practically approach such found lower boundaries. Minimal prefix…

Information Theory · Computer Science 2012-07-10 Jarek Duda

Key Encapsulation Mechanisms (KEMs) are a set of cryptographic techniques that are designed to provide symmetric encryption key using asymmetric mechanism (public key). In the current study, we concentrate on design and analysis of key…

Cryptography and Security · Computer Science 2024-12-09 Reza Hooshmand

Frequency estimation data structures such as the count-min sketch (CMS) have found numerous applications in databases, networking, computational biology and other domains. Many applications that use the count-min sketch process massive and…

Data Structures and Algorithms · Computer Science 2018-05-01 Mayank Goswami , Dzejla Medjedovic , Emina Mekic , Prashant Pandey

We present a new approach for computing compact sketches that can be used to approximate the inner product between pairs of high-dimensional vectors. Based on the Weighted MinHash algorithm, our approach admits strong accuracy guarantees…

Sketching is a randomized dimensionality-reduction method that aims to preserve relevant information in large-scale datasets. Count sketch is a simple popular sketch which uses a randomized hash function to achieve compression. In this…

Machine Learning · Statistics 2019-11-05 Yang Shi , Animashree Anandkumar

We present one-shot compression protocols that optimally encode ensembles of $N$ identically prepared mixed states into $O(\log N)$ qubits. In contrast to the case of pure-state ensembles, we find that the number of encoding qubits drops…

Quantum Physics · Physics 2016-03-02 Yuxiang Yang , Giulio Chiribella , Daniel Ebler

Two widely used randomized algorithms are the sketch-and-solve method for least-squares regression and the randomized SVD for low-rank approximation. These algorithms apply a random embedding to compress a target matrix, and they perform…

Numerical Analysis · Mathematics 2026-05-20 Ethan N. Epperly , Robert J. Webber

Let $X$ be a set of $n$ points of norm at most $1$ in the Euclidean space $R^k$, and suppose $\varepsilon>0$. An $\varepsilon$-distance sketch for $X$ is a data structure that, given any two points of $X$ enables one to recover the square…

Metric Geometry · Mathematics 2017-04-04 Noga Alon , Bo'az Klartag

Randomised algorithms often employ methods that can fail and that are retried with independent randomness until they succeed. Randomised data structures therefore often store indices of successful attempts, called seeds. If $n$ such seeds…

Data Structures and Algorithms · Computer Science 2025-07-03 Hans-Peter Lehmann , Peter Sanders , Stefan Walzer , Jonatan Ziegler

This paper presents a novel achievable scheme for coded caching systems with $N$ files and $K$ users, specifically when $N \leq K$. This new scheme employs linear coding both during the placement phase - where cache contents are linear…

Information Theory · Computer Science 2024-06-11 Yinbin Ma , Daniela Tuninetti

Recently, Czumaj et.al. (arXiv 2017) presented a parallel (almost) $2$-approximation algorithm for the maximum matching problem in only $O({(\log\log{n})^2})$ rounds of the massive parallel computation (MPC) framework, when the memory per…

Data Structures and Algorithms · Computer Science 2017-09-15 Sepehr Assadi

In recent network architectures, multi-MEC cooperative caching has been introduced to reduce the transmission latency of VR videos, in which MEC servers' computing and caching capability are utilized to optimize the transmission process.…

Networking and Internet Architecture · Computer Science 2023-03-09 Jingwen Xia , Luyao Chen , Yong Tang , Ting Yang , Wenyong Wang

Conventional embedding methods directly associate each symbol with a continuous embedding vector, which is equivalent to applying a linear transformation based on a "one-hot" encoding of the discrete symbols. Despite its simplicity, such…

Machine Learning · Computer Science 2018-06-26 Ting Chen , Martin Renqiang Min , Yizhou Sun